Direct observation of negative cooperativity in a detoxification enzyme at the atomic level by Electron Paramagnetic Resonance spectroscopy and simulation

Abstract

The catalytic activity of human glutathione S‐transferase A1‐1 (hGSTA1‐1), a homodimeric detoxification enzyme, is dependent on the conformational dynamics of a key C‐terminal helix α9 in each monomer. However, the structural details of how the two monomers interact upon binding of substrates is not well understood and the structure of the ligand‐free state of the hGSTA1‐1 homodimer has not been resolved. Here, we used a combination of EPR distance measurements and weighted ensemble simulations to characterize the conformational ensemble of the ligand‐free state at the atomic level. EPR measurements reveal a broad distance distribution between a pair of Cu(II) labels in the ligand‐free state that gradually shifts and narrows as a function of increasing ligand concentration. These shifts suggest changes in the relative positioning of the two α9 helices upon ligand binding. Weighted ensemble simulations generated unbiased pathways for the seconds‐timescale transition between alternate states of the enzyme, leading to the generation of atomically detailed structures of the ligand‐free state. Notably, the simulations provide direct observations of negative cooperativity between the monomers of hGSTA1‐1, which involve the mutually exclusive docking of α9 in each monomer as a lid over the active site. We identify key interactions between residues that lead to this negative cooperativity. Negative cooperativity may be essential for interaction of hGSTA1‐1 with a wide variety of toxic substrates and their subsequent neutralization. More broadly, this work demonstrates the power of integrating EPR distances with weighted ensemble rare‐events sampling strategy to gain mechanistic information on protein function at the atomic level.This article is protected by copyright. All rights reserved.

Modeling of Cu(ii)-based protein spin labels using rotamer libraries

“…It is also instructive to compare the predicted distribution widths with experiments. 55,60,72 For GB1, the predicted widths are close to the experimental results. GB1 has limited backbone fluctuations 61,74–76 and therefore this protein serves as an important test case to establish the robustness of the analysis.…”

“…To evaluate the accuracy of the dHis-Cu( ii )-NTA rotamer libraries as well as the chiLife bifunctional label modeling method, we modeled dHis-Cu( ii )-NTA on 7 sites on 3 proteins and compared the predicted distance distributions to previously published experimentally derived distributions between site pairs on the GB1 domain of protein G, human glutathione S-transferase A1 (hGSTA1), and Yersinia outer protein O (YopO). 55,60,72 This analysis is shown in Fig. 5.…”

“…While over-smoothing due to low signal-to-noise ratio (SNR) can result in such broadenings, this does not apply to the original signal for hGSTA1-1 and YopO, which have high SNR. 55,72 Therefore, the broader distances are likely from the flexible protein backbones that we cannot model from a single PDB structure. In the case of Fig.…”

“…For Q-band data (all YopO data and hGSTA1), we summed DEER traces at three field positions 55,72 to eliminate orientational selection and performed background correction by subtracting a 3rd-order polynomial which was fit to the last ¾ of the time-domain signal. The summed and background corrected data were fit using model-free Tikhonov regularization with only the modulation depth as a nonlinear parameter, i.e.…”

Pulse Dipolar Electron Paramagnetic Resonance Spectroscopy Distance Measurements at Low Nanomolar Concentrations: The CuII-Trityl Case

“…Furthermore, the dHis-CuNTA labeling has been shown to be robust against competing ligands and to retain its high affinity binding over a wide pH range, thus demonstrating biologically relevant compatibility . While a majority of the benchmarking studies on dHis-CuNTA have been performed on different constructs of a model protein (GB1, vide infra ), this labeling approach has also been applied to a variety of more complex biological systems. ,, Despite its vulnerability to reduction, CuNTA has been used for in-cell PDS …”